Recently, high resolution LIDAR (Light Detection And Ranging) scans of terrain data have been collected using air and ground based scanners. LIDAR is an optical remote sensing technology that measures properties of scattered light to find range and/or other information of a distant target utilizing laser pulses to determine distance to an object or surface. Like the radar technology, which uses radio waves, the range to an object is determined by measuring the time delay between transmission of a pulse and detection of the reflected signal. LIDAR technology has application in archaeology, geography, geology, geomorphology, seismology, remote sensing and three-dimensional (3D) mapping.
A point cloud is a set of vertices in a three-dimensional coordinate system, which is often created by three-dimensional scanners, such as LIDAR systems which measure a large number of points on the surface of an object, and output the point cloud as a data file. The point cloud is a collection of three-dimensional spatial points, represents the visible surface of the object that has been scanned or digitized. For example in FIG. 1, a scatter plot of point cloud data from the scan of the “Happy Buddha” includes 543,652 points in the point cloud, which may cause storage and transmission of such huge data problematic.
U.S. Pat. No. 7,215,430 to Kacyra et al. discloses an integrated system for generating a model of a three-dimensional object, wherein a scanning laser device scans the three-dimensional object and generates a point cloud, a model is generated, responsive to the point cloud, representing constituent geometric shapes of the object, and a data file is generated, responsive to the model, which can be inputted to a computer-aided design system. Kacyra also discloses compression of video images. However, Kacyra does not disclose anything related to using the level set method to compress the point cloud data and store the data in a form of gradient, and to decompress the gradient data to accurately generate a point cloud which approximates the scanned point cloud.
U.S. Pat. No. 6,922,234 to Hoffman et al. discloses a method and apparatus to document the spatial relationships and geometry of existing buildings and structures. More specifically, Hoffman discloses a method and apparatus comprising a 3D camera (scanning laser range finder) which can produce high resolution reflectance images, a magnetic storage device which can store scanned measurement data, a set of algorithms which are used to interpret the measurement data, and a software interface which allows a human to interact and query the measurement information in useful ways. Like Kacyra, Hoffman does not disclose anything related to using the level set method to compress the point cloud data and store the data in a form of gradient, and to decompress the gradient data to accurately generate a point cloud which approximates the scanned point cloud.
Therefore, there remains a need for a new and improved apparatus and method for not only generating the point cloud data, but also accurately compressing and reconstructing the point cloud to ease storage and transmission of the data.